Artificial Intelligence
人工智能技术的英语
人工智能技术的英语artificial intelligence technology常见释义：英[ˌɑːtɪˈfɪʃl ɪnˈtelɪdʒəns tekˈnɒlədʒi]美[ˌɑːrtɪˈfɪʃl ɪnˈtelɪdʒəns tekˈnɑːlədʒi]例句：虽然现在针对选择题和判断正误题的自动评分系统已经非常普遍，但利用人工智能技术对短文进行评分尚未得到教育工作者的广泛认可，而且批评声也很多。
Although automated grading systems for multiple-choice and true-false tests are now widespread, the use of artificial intelligence technology to grade essay answers has not yet received widespread acceptance by educators and has many critics.将CAD和人工智能技术引入组合夹具设计中，可以提高生产效率、减轻劳动强度、缩短生产准备周期和加快产品上市时间。
Introducing CAD and artificial intelligence technology into modular fixture design can improve production efficiency, lighten working intensity, reduce manufacturing lead-time and marketing time.听上去够酷的了，不过该公司已经开始研发包含摄像头和人工智能技术的升级版鞋子，不仅可以探测到障碍物，还可以检测出是何种障碍物。
That sounds impressive enough, but the company is already working on a much more advanced version that incorporates cameras and artificial intelligence to not only detectobstacles but also their nature.Java语言特点及其对人工智能技术的影响和促进Characteristics of Java Language and the Action of Influence and Promotion of it for AI Technology。
2022年人工智能的英语作文_artificial intelligence 4篇_1
人工智能的英语作文_artificial intelligence 4篇导读：关于”人工智能“的英语作文范文4篇，作文题目：artificial intelligence。
以下是关于人工智能的专八英语范文，每篇作文均为真题范文带翻译。
关于”人工智能“的英语作文范文4篇，作文题目：artificial intelce。
以下是关于人工智能的专八英语范文，每篇作文均为真题范文带翻译。
高分英语作文1：artificial intelceOne of the future trends of computer science is artificial intelce, which is the research and artificial simulation of human thinking, and ultimately can make human like to use the same machine to serve human beings and help people solve problems. After all, people think that it is unique, emotional, and has a variety of personalities, which is very difficult to achieve mechanically. To be like the human thinking machine, it is the only kind of artificial intelce.It is not all through the research of artificial intelce, which can solve various scientific problems and promote the development of other sciences. Artificial intelce is the best. I believe that artificial intelce is the best Learning is waiting for human beings to explore its real connotation step by step.中文翻译：计算机科学的未来趋势之一是人工智能，它是对人类思维的研究和人工模拟，最终能够使人类喜欢用同样的机器为人类服务并帮助人们解决问题。
1-7 Artificial Intelligence(AI)
systems that learn new concepts and tasks ,systems that can reason and draw useful conclusions about the world around us, systems that can understand a natural language or perceive and comprehend a visual scene, and systems that perform
确实，在不同地执行某些任 务中它们会实际上超过人的 一些能力。重要的一点是这 些系统都能有效而高效率地 执行智能任务。
Key words: exceed [ɪkˈsi:d] vt. 超过; 超越; 胜过
它具体体现了有意识地和无 意识地通过学习和经验获得 的所有知识和技艺：高度精 确的视觉和听觉感知；思维； 想象；交谈、读、写、驾车、 记忆和回忆事实、表达和感 受情感的能力，以及更多。
Expanded vocabulary: embody [ɪmˈbɒdi] vt. 表现 conscious [ˈkɒnʃəs] adj. 有意识的 refine[rɪˈfaɪn] vt. 提炼; 改善
1-7Artificial Intelligence(AI)
In spite of these impressive achievements,
we still have not been able to produce co-
ordinated, autonomous systems which
1-7Artificial Intelligence(AI)
Can we ever expect to build systems which exhibit these characteristics? The answer to this question is yes! Systems have already been developed to perform many types of intelligent tasks, and expectations are high for near term development of even more impressive systems. We now have systems which can learn from examples, from being told, from past related experiences, and through reasoning.
Artificial Intelligence 第一章 人工智能的基本概念(导论) 《人工智能》课件
第三节 人工智能的研究目标
AI的研究目标分近期目标和远期目标：
近期目标：研究如何使计算机去做那些过去只有靠
人的智力才能完成的工作。
远期目标：研究如何利用自动机去模拟人的某些思
可用模型 进行评价
2.智能的要素：
最重要的要素包括：适应环境、适应偶然性事件、能分 辩模糊的或矛盾的信息，在孤立的情况中找出相似性，产生新 概念和新思想。
3.智能的分类：
自然智能 有规律的智能行为：计算机能解决
人工智能 无规律的智能行为：如洞察力、创造力。 关于这些问题：计算机还不能解决。
三、如何判定智能？
第五节 AI的发展简史
第一阶段：孕育期（1956年以前） 第 二 阶 段 ： AI 的 基 础 技 术 的 研 究 和 形 成 时 期 1956— 1970 第 三 阶 段 ： AI 发 展 和 实 用 阶 段 （ 专 家 系 统 ） 1971— 1980 第四阶段：知识工程与机器学习发展阶段1981—1990 第五阶段：智能综合集成阶段,二十世纪90年代至今，
英国自然杂志主编坎贝尔博士说：目前信息技术和生命科学 有交叉融合的趋势，比如AI的研究就需要从生命科学的角度揭 开大脑思维的机理，需要利用信息技术模拟实现这种机理。 （参考文献：李凡长、佘玉梅：Agent的遗传算法研究，《计 算机科学》）
3.行为主义（Actionism）：
又 称 进 化 主 义 （ Evolutionism ） 或 控 制 论 学 派 （Cyberneticisism）。其原理为控制论及感知再到动作型控 制系统。主要进行行为模拟，代表人物：布鲁克斯等。
人工智能英语缩写及应用
人工智能英语缩写及应用人工智能（Artificial Intelligence，简称AI）是一门研究如何使计算机系统完成类似于人类智能的任务的领域。
以下是AI的英语缩写及其应用：1.AI - Artificial Intelligence：人工智能，是指通过模拟、延伸人类智能的方式赋予计算机系统学习、理解、推理、规划、感知等能力的科学和工程。
2.ML - Machine Learning：机器学习，是AI的一个分支，致力于开发能够自动学习和改进的算法。
3.DL - Deep Learning：深度学习，是机器学习的一种特殊形式，使用神经网络进行复杂的模式识别和决策任务。
4.NLP - Natural Language Processing：自然语言处理，是一种使计算机能够理解、解释和生成人类语言的技术。
5.CV - Computer Vision：计算机视觉，是一种使计算机系统能够理解和解释图像和视频的技术。
6.ASR - Automatic Speech Recognition：自动语音识别，是一种使计算机能够识别和理解语音的技术。
7.IoT - Internet of Things：物联网，是通过互联网连接各种设备，使它们能够收集和交换数据的概念。
8.AIoT - Artificial Intelligence of Things：物联网中的人工智能，是将人工智能技术应用于物联网设备，使其更加智能化。
9.RPA - Robotic Process Automation：机器人流程自动化，是使用软件机器人或“机器人”自动执行重复性业务流程的技术。
10.A GI - Artificial General Intelligence：人工通用智能，是一种具有与人类相似广泛认知能力的理论AI形态。
11.A IaaS - AI as a Service：人工智能即服务，是通过云服务提供商提供的云端人工智能服务。
人工智能
人工智能（Artificial Intelligence），英文缩写为AI。
它是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学。
人工智能是计算机科学的一个分支，它企图了解智能的实质，并生产出一种新的能以人类智能相似的方式做出反应的智能机器，该领域的研究包括机器人、语言识别、图像识别、自然语言处理和专家系统等。
人工智能从诞生以来，理论和技术日益成熟，应用领域也不断扩大，可以设想，未来人工智能带来的科技产品，将会是人类智慧的“容器”。
人工智能可以对人的意识、思维的信息过程的模拟。
人工智能不是人的智能，但能像人那样思考、也可能超过人的智能。
人工智能是一门极富挑战性的科学，从事这项工作的人必须懂得计算机知识，心理学和哲学。
人工智能是包括十分广泛的科学，它由不同的领域组成，如机器学习，计算机视觉等等，总的说来，人工智能研究的一个主要目标是使机器能够胜任一些通常需要人类智能才能完成的复杂工作。
但不同的时代、不同的人对这种“复杂工作”的理解是不同的。
人工智能（Artificial Intelligence），英文缩写为AI。
它是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学。
人工智能是计算机科学的一个分支，它企图了解智能的实质，并生产出一种新的能以人类智能相似的方式做出反应的智能机器，该领域的研究包括机器人、语言识别、图像识别、自然语言处理和专家系统等。
人工智能从诞生以来，理论和技术日益成熟，应用领域也不断扩大，可以设想，未来人工智能带来的科技产品，将会是人类智慧的“容器”。
人工智能可以对人的意识、思维的信息过程的模拟。
人工智能不是人的智能，但能像人那样思考、也可能超过人的智能。
人工智能是一门极富挑战性的科学，从事这项工作的人必须懂得计算机知识，心理学和哲学。
人工智能是包括十分广泛的科学，它由不同的领域组成，如机器学习，计算机视觉等等，总的说来，人工智能研究的一个主要目标是使机器能够胜任一些通常需要人类智能才能完成的复杂工作。
ARTIFICIAL INTELLIGENCE——人工智能(英文)
ARTIFICIAL INTELLIGENCE——人工智能1 Artificial intelligence (AI) is, in theory, the ability of an artificial mechanism to demonstrate some form of intelligent behavior equivalent to the behaviors observed in intelligent living organisms. Artificial intelligence is also the name of the field of science and technology in which artificial mechanisms that exhibit behavior resembling intelligence are developed and studied.2 The term AI itself, and the phenomena actually observed, invite --- indeed demand --- philosophical speculation about what in fact constitutes the mind or intelligence. These kinds of questions can be considered separately, however, from a description of the various endeavors to construct increasingly sophisticated mechanisms that exhibit “intelligence.”3 Research into all aspects of AI is vigorous. Some concern exists among workers in the field, however, that both the progress and expectations of AI have been overstated. AI programs are primitive when compared to the kinds of intuitive reasoning and induction of which the human brain or even the brains of much less advanced organisms are capable. AI has indeed shown great promise in the area of expert systems --- that is, knowledge-based expert programs --- but while these programs are powerful when answering questions within a specific domain, they are nevertheless incapable of any type of adaptable, or truly intelligent, reasoning.4 Examples of AI systems include computer programs that perform such tasks as medical diagnoses and mineral prospecting. Computers have also been programmed to display some degree of legal reasoning, speech understanding, vision interpretation, natural-language processing, problem solving, and learning. Although most of these systems have proved valuable either as research vehicles or in specific, practical applications, most of them are also still very far from being perfected.5 CHARACTERISTICS OF AI: No generally accepted theories have yet emerged within the field of AI, owing in part to the fact that AI is a very young science. It is assumed, however, that on the highest level an AI system must receive input from its environment, determine an action or response, and deliver an output to its environment. A mechanism for interpreting the input is needed. This need has led to research in speech understanding, vision, and natural language. The interpretation must be represented in some form that can be manipulated by the machine.6 In order to achieve this goal, techniques of knowledge representation are invoked. The AI interpretation of this, together with knowledge obtained previously, ismanipulated within the system under study by means of some mechanism or algorithm. The system thus arrives at an internal representation of the response or action. The development of such processes requires techniques of expert reasoning, common-sense reasoning, problem solving, planning, signal interpretation, and learning. Finally, the system must网construct an effective response. This requires techniques of natural-language generation.7 THE FIFTH-GENERATION ATTEMPT: In the 1980s, in an attempt to develop an expert system on a very large scale, the Japanese government began building powerful computers with hardware that made logical inferences in the computer language PROLOG. (Following the idea of representing knowledge declaratively, the logic programming PROLOG had been developed in England and France. PROLOG is actually an inference engine that searches declared facts and rules to confirm or deny a hypothesis. A drawback of PROLOG is that it cannot be altered by the programmer.) The Japanese referred to such machines as “fifth-generation” computers.8 By the early 1990s, however, Japan had forsaken this plan and even announced that they were ready to release its software. Although they did not detail reasons for their abandonment of the fifth-generation program, U.S scientists faulted their efforts at AI as being too much in the direction of computer-type logic and too little in the direction of human thinking processes. The choice of PROLOG was also criticized. Other nations were by then not developing software in that computer language and were showing little further enthusiasm for it. Furthermore, the Japanese were not making much progress in parallel processing, a kind of computer architecture involving many independent processors working together in parallel—a method increasingly important in the field of computer science. The Japanese have now defined a “sixth-generation” goal instead, called the Real World Computing Project, that veers away from the expert-systems approach that works only by built-in logical rules.9 THE FUTURE OF AI RESEARCH: One impediment to building even more useful expert systems has been, from the start, the problem of input---in particular, the feeding of raw data into an AI system. To this end, much effort has been devoted to speech recognition, character recognition, machine vision, and natural-language processing. A second problem is in obtaining knowledge. It has proved arduous toextract knowledge from an expert and then code it for use by the machine, so a great deal of effort is also being devoted to learning and knowledge acquisition.10 One of the most useful ideas that has emerged from AI research, however, is that facts and rules (declarative knowledge) can be represented separately from decision-making algorithms (procedural knowledge). This realization has had a profound effect both on the way that scientists approach problems and on the engineering techniques used to produce AI systems. By adopting a particular procedural element, called an inference engine, development of an AI system is reduced to obtaining and codifying sufficient rules and facts from the problem domain. This codification process is called knowledge engineering. Reducing system development to knowledge engineering has opened the door to non-AI practitioners. In addition, business and industry have been recruiting AI scientists to build expert systems.11 In particular, a large number of these problems in the AI field have been associated with robotics. There are, first of all, the mechanical problems of getting a machine to make very precise or delicate movements. Beyond that are the much more difficult problems of programming sequences of movements that will enable a robot to interact effectively with a natural environment, rather than some carefully designed laboratory setting. Much work in this area involves problem solving and planning.12 A radical approach to such problems has been to abandon the aim of developing “reasoning” AI systems and to produce, instead, robots that function “reflexively”. A leading figure in this field has been Rodney Brooks of the Massachusetts Institute of Technology. These AI researchers felt that preceding efforts in robotics were doomed to failure because the systems produced could not function in the real world. Rather than trying to construct integrated networks that operate under a centralizing control and maintain a logically consistent model of the world, they are pursuing a behavior-based approach named subsumption architecture.13 Subsumption architecture employs a design technique called “layering,”---a form of parallel processing in which each layer is a separate behavior-producing network that functions on its own, with no central control. No true separation exists, in these layers, between data and computation. Both of them are distributed over the same networks. Connections between sensors and actuators in these systems are kept short as well. The resulting robots might be called “mindless,” but in fact they have demonstrated remarkable abilities to learn and to adapt to real-life circumstances.14 The apparent successes of this new approach have not convinced many supporters of integrated-systems development that the alternative is a valid one for drawing nearer to the goal of producing true AI. The arguments that have arisen between practitioners of the two different methodologies are in fact profound ones. They have implications about the nature of intelligence in general, whether natural or artificial。
人工智能(artificial intelligence, AI)
人工智能(artificial intelligence, AI)人工智能（artificial intelligence, AI）人工智能（Artificial Intelligence，简称AI）是一门研究如何使计算机具有类似人类智能的能力的科学与技术领域。
它利用计算机科学、数学、逻辑学、控制论等多个学科的理论和方法，旨在开发可以执行人类智能任务的计算机系统。
随着计算机技术和处理能力的不断提升，人工智能正逐渐融入我们的日常生活，并在各行各业带来革命性的变革。
一、人工智能的发展历程人工智能的发展可以追溯到上世纪50年代。
在那个时期，人们开始尝试用计算机模拟人脑的思维过程。
随着计算机技术的进步，人工智能逐渐开始崭露头角。
20世纪80年代，专家系统成为人工智能的主要研究方向。
90年代，机器学习和数据挖掘等技术逐渐兴起，为人工智能的发展带来新的突破。
最近几年，深度学习技术的出现，使得人工智能在图像识别、语音识别、自然语言处理等领域取得了巨大的成功。
二、人工智能的应用领域人工智能已经广泛应用于各个领域，为我们的生活带来了诸多便利。
在医疗领域，人工智能可以帮助医生进行疾病诊断和治疗方案制定；在交通领域，人工智能可以优化路况并提供实时导航服务；在金融领域，人工智能可以进行风险评估和交易分析等工作。
此外，人工智能还在教育、农业、能源等领域发挥着重要的作用。
三、人工智能的挑战与展望人工智能的快速发展给我们的社会和生活带来了前所未有的改变，但同时也面临着一些挑战。
首先，人工智能的智能水平仍然有限，无法完全达到人类的智能水平；其次，人工智能在取得成功的同时，也带来了一些伦理和法律问题，例如隐私保护和人工智能算法的公平性等。
未来，我们需要继续加强对人工智能技术的研究，推动人工智能与人类社会的和谐共存。
结语人工智能作为一门前沿科技，正在改变着我们的世界。
它不仅为我们提供了更多的便利，也给我们带来了许多新的机遇和挑战。
人工智能名词解释考研
人工智能名词解释考研Artificial Intelligence Terminology Explanation for Postgraduate Entrance Examination人工智能（Artificial Intelligence）是计算机科学的一个重要领域，致力于通过模拟和复制人类智能的方式，使计算机能够具备类似于人类的思维和行为能力。
随着科技的不断进步，人工智能已经成为考研中一个重要的知识点。
以下是一些与人工智能有关的重要名词解释。
1. 机器学习（Machine Learning）：是人工智能的一个关键领域，旨在通过让计算机从数据中获取知识和经验，从而使其不需要明确编程即可自动进行学习和改进。
机器学习算法主要分为监督学习、无监督学习和强化学习。
2. 深度学习（Deep Learning）：是机器学习的一个分支，通过构建和模拟人脑的神经网络，使计算机能够进行更深入、更复杂的学习和分析。
深度学习广泛应用于图像识别、语音识别以及自然语言处理等领域。
3. 自然语言处理（Natural Language Processing）：是人工智能的一个重要组成部分，用于使计算机能够理解、分析和处理人类的自然语言。
自然语言处理涉及词法分析、句法分析、语义理解等技术，广泛应用于机器翻译、智能客服等领域。
4. 计算机视觉（Computer Vision）：是使计算机能够通过图像和视频来感知和理解世界的能力。
计算机视觉的应用包括图像识别、目标检测和图像生成等领域。
5. 自动驾驶（Autonomous Driving）：是人工智能技术在汽车领域的一种应用，通过传感器和算法，使汽车能够自动感知环境、理解路况并自主行驶。
自动驾驶技术涉及机器学习、计算机视觉等多个领域。
6. 人工智能伦理学（Ethics of Artificial Intelligence）：是研究人工智能技术对社会和人类的影响以及相应伦理问题的学科。
living with artificial intelligence解析
living with artificial intelligence解析
"Living with Artificial Intelligence" 这个短语的含义是“与人工智能一起生活”。
在这个短语中，"Artificial Intelligence" 指的是人工智能技术，这是一种能够模仿人类智能的技术。
而"living with" 则表示与人工智能技术一起生活，意味着人们已经将人工智能技术融入到了日常生活中。
这个短语可以用来描述人们如何利用人工智能技术来改善生活质量，例如通过智能家居设备控制家庭环境，使用智能语音助手进行语音搜索和信息查询，以及使用智能医疗设备来监测健康状况等。
同时，这个短语也可以用来探讨人工智能技术对人类社会的影响，例如人工智能技术可能带来的就业机会和职业变革，以及人工智能技术可能带来的隐私和安全问题等。
总之，"Living with Artificial Intelligence" 这个短语描述了人们与人工智能技术相互融合的生活方式，以及这种生活方式所带来的机遇和挑战。
Artificial intelligence人工智能(口语课)
Artificial intelligence(口语课)Artificial Intelligence (口语课)1.介绍1.1 什么是？是一门研究如何使计算机可以执行类似于人类智能的任务的科学与工程领域。
它涵盖了包括机器学习、自然语言处理、感知、推理和决策等多个方面。
1.2 为什么学习？已经成为现代社会中一个重要的领域，掌握的基础知识能够帮助我们应对各种实际问题，并在未来职业发展中具备竞争力。
2.技术2.1 机器学习①监督学习监督学习是指通过给机器提供带有标签的数据集来训练模型，然后用该模型来预测未标记数据的标签。
②无监督学习无监督学习是指通过给机器提供不带有标签的数据集来训练模型，让机器自己发现数据中的模式和规律。
③强化学习强化学习是指通过给机器提供一个环境和一些奖励信号，让机器通过不断尝试和学习来最大化累积奖励。
2.2 自然语言处理自然语言处理是指研究如何让机器能够理解、分析和人类语言的技术。
它包括语言识别、语言理解、语言等多个方面。
2.3 计算机视觉计算机视觉是指研究如何使机器能够理解和解释视觉信息的技术。
它包括图像识别、物体检测、图像等多个方面。
3.应用3.1 自动驾驶自动驾驶技术利用技术，使汽车能够自主地感知周围环境、做出决策和执行行动，实现无人驾驶。
3.2 人脸识别人脸识别技术利用技术，通过分析和比对人脸图像来识别身份，广泛应用于安全监控、方式解锁等领域。
3.3 语音语音利用技术，通过语音交互来提供信息和执行命令，被广泛应用于智能音箱、方式等设备中。
4.的伦理和社会问题4.1 数据隐私随着的发展，个人数据的收集和使用已成为一个重要的伦理和社会问题，需要制定合适的法律和政策来保护个人隐私权。
4.2 就业问题的广泛应用可能导致一些职业被取代，需要思考如何解决失业问题和实现职业转型。
4.3 道德问题在做出决策时可能面临道德困境，需要研究如何使机器能够做出合乎道德标准的决策。
附件：无法律名词及注释：1.数据隐私：个人数据的隐私权保护，包括个人信息的收集、存储、使用和共享等方面的法律规定。
人工智能名词解释
人工智能名词解释人工智能（Artificial Intelligence，简称AI），是指模拟、延伸和扩展人类智能的一门科学与技术。
它旨在研究和开发能够模仿、执行人类智能任务的智能系统。
人工智能的发展涉及多个子领域，包括机器学习、自然语言处理、计算机视觉和专家系统等。
下面将逐个解释这些与人工智能相关的名词。
1. 机器学习（Machine Learning）机器学习是人工智能的一个重要分支，它涉及让计算机通过从大量数据中学习、识别模式并进行预测和决策的能力。
机器学习算法通过对训练数据进行分析和学习，从而能够自主地改善和适应新数据，实现模型的自动调整和优化。
2. 自然语言处理（Natural Language Processing，简称NLP）自然语言处理是人工智能领域关注的一个重要方向，它涉及让计算机能够理解、分析和生成人类语言。
通过使用自然语言处理技术，计算机可以实现自动的文本理解、问答系统、机器翻译和情感分析等任务。
3. 计算机视觉（Computer Vision）计算机视觉是人工智能中的一个子领域，研究和开发让计算机能够理解和解释图像和视频的能力。
计算机视觉技术可以实现图像识别、目标检测、人脸识别和图像生成等任务，打开了计算机与视觉世界之间的交互通道。
4. 专家系统（Expert System）专家系统是一类基于知识和推理的人工智能系统，它通过模拟和应用人类专家的知识和经验来解决复杂的问题。
专家系统通过与用户的交互，推理和提供问题解决方案，可广泛用于医疗、金融、工业等领域的决策支持和问题求解。
5. 深度学习（Deep Learning）深度学习是机器学习领域中一种特殊的算法，其核心思想是构建和训练具有多个层次和参数的神经网络模型。
深度学习通过模拟人脑神经元之间的连接方式，实现了对复杂数据的高级抽象和表征，广泛应用于图像和语音识别、自动驾驶和自然语言处理等领域。
6. 强化学习（Reinforcement Learning）强化学习是一种机器学习的方法，通过建立智能体与环境的交互模型，以试错的方式逐步学习和改进行为策略。
人工智能(Artificial Intelligence)
威尔森的行动
• 他开始寻找机会跳出传统的AI圈子，了解 更多信息，并重新开始考虑努力的方向， 在开发一种简单的机器人。 • 他于1987年把他的人造生物取名为 “animations”，后来又简化为“animat （动化物）”。 • 在较短的时间内，在美国甚至欧洲的人工 智能学者都开始纷纷议论起这个“人工智 能动化物”。
从模拟人的思想的角度来考虑
• 当时有的学者把AI的研究途径概括为以符号处理 为核心的传统方法及网络连接为主的连接机制 （Connectionism）方法。 • 人的两种主要思维方式是逻辑思维和形象思维 （直感思维）。 • 符号处理可以认为主要在于模拟人的逻辑思维， 连接机制主要致力于模拟人的形象思维。 • 关于形象思维虽然人们认识到它的重要性，但用 现在的计算机来模拟形象思维是很困难的，需要 在计算机的体系结构上有新的突破。
四个概念：智能与涌现
• ③ 智能（intelligence) ：机器人看起来有 智能行为。智能的来源不仅仅限于计算装 置，也来自周围的情景、敏感器之间的信 息传送以及机器人与周围环境的交互作用。 对于智能的来源与传统的说法不大一样。 • ④ 涌现（emergence) ：智能是由很多部 件交互作用、与环境交互作用所产生的系 统涌现出来的总的行为。
Artificial Intelligence 人 工 智 能
第4章 适应性智能系统
• 4.1人工智能发展的几个阶段 • 4.2智能系统 • 4.3智能控制
– 智能交通 – 智能家居 – 智能楼宇
4.1人工智能发展的几个阶段
• 早期人工智能（AI）的起源是基于心理学 的研究，寻求启发式知识在人类思维过程 中的作用，把这类知识表达成逻辑形式加 以利用。 • 这是AI最早的模型。早期以逻辑为基础的 AI研究，可以概括为符号表达、启发式编 程、逻辑推理或者称为“深思熟虑”的思 维的模型，这可以说是AI研究的最初阶段， 或称传统的AI时期。
artificial词组
以下是一些与“artificial”相关的常见词组：
1. Artificial intelligence（人工智能）：指模拟人类智能的技术和系统，涵盖机器学习、自然语言处理等多个领域。
2. Artificial neural network（人工神经网络）：模拟生物神经网络的计算模型，用于处理和识别复杂的模式。
3. Artificial life（人工生命）：研究如何通过计算机模拟和生成生命现象的学科。
4. Artificial retina（人工视网膜）：用于替代或辅助受损视网膜的技术和设备。
5. Artificial skin（人工皮肤）：用于修复或替换受损皮肤的生物医学材料。
6. Artificial heart（人工心脏）：用于替代或辅助自然心脏的医疗设备。
7. Artificial organ（人工器官）：模拟自然器官功能的医疗设备或技术。
8. Artificial pancreas（人工胰腺）：用于监测和控制糖尿病病情的医疗设备。
9. Artificial limb（假肢）：用于替代失去的肢体的设备，包括假手、假脚等。
10. Artificial tooth（假牙）：用于替代失去的牙齿的医疗设备。
请注意，这些只是一些示例，并不包含与“artificial”相关的所有词组。
如需更多信息，建议查阅英文词典或相关书籍。
人工智能ai英文介绍
人工智能ai英文介绍Artificial Intelligence (AI): An IntroductionIn the era of rapid technological advancements, artificial intelligence (AI) stands as one of the most exciting and transformative fields. AI refers to the simulation of human intelligence in machines that are programmed to think and learn, enabling them to perform tasks typically requiring human cognition. This article serves as an introduction to AI, discussing its definition, applications, and potential impact on various industries.1. Definition of Artificial IntelligenceAI is a branch of computer science that focuses on creating intelligent machines capable of mimicking human behavior. It involves developing algorithms and models that enable computers to process information, reason, learn, and make decisions. The ultimate goal of AI is to build machines that not only perform tasks but also possess a level of intelligence similar to or surpassing human intelligence.2. History of Artificial IntelligenceThe concept of AI emerged in the 1950s when researchers began exploring the idea of creating machines that can imitate human thinking. The field progressed through various stages, from early rule-based systems to modern machine learning algorithms. Significant milestones in AI history include the development of expert systems, neural networks, and the recent breakthroughs in deep learning.3. Types of Artificial IntelligenceAI can be categorized into two main types: Narrow AI and General AI. Narrow AI, also known as Weak AI, refers to AI systems designed for specific tasks, such as voice assistants or autonomous vehicles. General AI, on the other hand, represents a hypothetical form of AI that possesses the ability to understand, learn, and perform any intellectual task that a human being can do.4. Applications of Artificial IntelligenceAI has found applications across various industries and domains. In healthcare, AI is utilized for medical diagnosis, drug discovery, and personalized treatment plans. In finance, AI is used for algorithmic trading, fraud detection, and risk assessment. Other sectors benefiting from AI include transportation, manufacturing, customer service, and agriculture.5. Impact of Artificial Intelligence on SocietyThe widespread adoption of AI brings both opportunities and challenges. On one hand, AI has the potential to enhance productivity, automate mundane tasks, and improve decision-making. On the other hand, concerns arise regarding job displacement, ethical implications, and biases in AI systems. Striking a balance between technological progress and societal well-being is a crucial consideration for the future of AI.6. Future Trends in Artificial IntelligenceThe future of AI holds immense potential for advancements. Some emerging trends include the integration of AI with other technologies like Internet of Things (IoT) and robotics, the development of explainable AI for transparency, and the focus on ethical AI design. Continued research anddevelopment will drive further innovation and push the boundaries of what AI can achieve.In conclusion, artificial intelligence is a fascinating field that revolutionizes how machines interact and respond to tasks, rivalling human intelligence. This article provided an overview of AI, discussing its definition, history, types, applications, societal impact, and future trends. As AI continues to evolve, it is essential to ensure its ethical and responsible adoption in order to harness its full potential for the benefit of society.。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
Artificial Intelligence
1.What is Artificial Intelligence ?
Broadly speaking, artificial intelligence is about the creation of human intelligent behavior, and intelligent behavior, including perception, reasoning, learning, communication, and behavior in a complex environment. Source: Nils J.Nilsson(1998).Artificial Intelligence A New Synthesis(pp.1)Elsevier
2.Artificial intelligence is how it affects human society ?
a.Employment issues
Due to a variety of artificial intelligence can replace the human mental, will make some people had to change their jobs, and even cause unemployment. Artificial Intelligence in science and engineering applications, make some people lose the opportunity to intervene information processing activities (such as planning, diagnosis, understanding and decision-making, etc.), and even had to change their way of working.
b.Changes in ways of thinking and ideas
Develop and promote the use of artificial intelligence, will affect the human way of thinking and
traditional ideas and make them change. For example, traditional knowledge is generally printed in books or newspapers and magazines, which are fixed, and knowledge but knowledge of artificial intelligence system is constantly revised, expanded and updated. Again, once the user expert system are beginning to believe the system (intelligent machines) judgments and decisions, then they may be reluctant to rack their brains become lazy and lose a lot of problems and solving tasks of responsibility and sensitivity. Students who over-reliance on calculators, and their proactive thinking and computing power will be significantly decreased. Excessive reliance on computer without any analysis suggested accepted, would make intelligent machine users cognitive decline and increased misunderstanding. In the design and development of intelligent systems, should take into account the above-mentioned problems, to encourage users to problem solving in the initiative, so that their active participation in the problem solving process intelligence.
c.Psychological threat
AI is also a part of the members of society feel
threatened psychological, or called spiritual threat. It is generally believed that only humans have a spiritual perception, and thus the machine with another. If one day, these people began to believe that the machine can also be thinking and creativity, then they may be disappointed, and even feel threatened. They worry: Someday, artificial intelligence machine intelligence will exceed human nature, humanity enslaved intelligent machines and intelligent systems.
d.Dangerous technologies out of control
The biggest danger than any new technology, it lost control of the human race, or is it falling into the hands of those who attempt to use the new technology against humanity. Some people worry that artificial intelligence, robotics and other threats to human security products. e.Legal problems
Application of artificial intelligence technology not only replaces the people some of the manual labor, but also some mental work instead of people, and sometimes even with the exercise of the functions served by people, will inevitably lead to legal disputes. Such as medical diagnosis expert system in case of mistakes, leading to
medical malpractice, how to deal with, whether the development of expert systems to be responsible, by the use of expert systems What is the responsibility, and so on.
Source:/jpkc2003/rengongzhine ng/rengongzhineng/kejian/AI/Ai/chapter1/152.htm
3.How to look at the future of artificial intelligence
The current development of artificial intelligence, human society has had a major impact.In the future for artificial intelligence, humans should develop a positive attitude to artificial intelligence, artificial intelligence service of humanity.
Source:/。